With the advancement of network technology and the coming of digital age, various network-based teaching models have emerged, such as live broadcast teaching and online teaching. Live broadcast teaching is also known as distance teaching, which instantly transmits the video and audio of a class to screens in classrooms or computers of students by holding a web conference. In this way, teachers and students can be in the same class without being at the same place. As for online teaching, all teaching materials are uploaded to a system platform so that students can select suitable material(s) to watch or listen after logging in the system platform.
Some of the conventional live broadcast teaching techniques have been able to return the images of the classroom or the students for teachers' reference. Usually, the returned images are from several places and contain several students' image. It is difficult for a teacher to interpret the returned images in a short time and, therefore, it is impossible for a teacher to timely (or even immediately) grasp the learning status of the students. In addition, most of the conventional online teaching platforms are unidirectional and, therefore, a teacher is unable to timely (or even immediately) learn the learning status of the students (for example, the learning outcomes, the gaze concentration, or even accurately watching). Most of the conventional online teaching platforms determine the learning outcomes of the students by giving post-class tests or questionnaires and, thus, it is impossible for teachers to timely (or even immediately) adjust the content of courses or the way of teaching courses.
To solve the aforesaid problems, there is a need for a technology that can timely (or even immediately) analyze and monitor the learning status of students so that teachers can timely (or even immediately) grasp the learning status of each of the students.